from __future__ import annotations

from collections.abc import MutableSequence




class   _UpperCamelCase :


			"""simple docstring"""






			def __init__(  self ,  lowerCAmelCase__ ,  lowerCAmelCase__		)	->   None:

							'''simple docstring'''


							if len(lowerCAmelCase__		) != degree + 1:
											raise ValueError(
											    '''The number of coefficients should be equal to the degree + 1.'''		)

							__lowercase					     =				list(lowerCAmelCase__		)
							__lowercase					     =				degree





			def __add__(  self ,  lowerCAmelCase__		)	->   Polynomial:

							'''simple docstring'''


							if self.degree > polynomial_a.degree:
											__lowercase					     =				self.coefficients[:]
											for i in range(polynomial_a.degree + 1		):
															coefficients[i] += polynomial_a.coefficients[i]
											return Polynomial(self.degree ,  lowerCAmelCase__		)
							else:
											__lowercase					     =				polynomial_a.coefficients[:]
											for i in range(self.degree + 1		):
															coefficients[i] += self.coefficients[i]
											return Polynomial(polynomial_a.degree ,  lowerCAmelCase__		)





			def __sub__(  self ,  lowerCAmelCase__		)	->   Polynomial:

							'''simple docstring'''


							return self + polynomial_a * Polynomial(0 ,  [-1]		)





			def __neg__(  self		)	->   Polynomial:

							'''simple docstring'''


							return Polynomial(self.degree ,  [-c for c in self.coefficients]		)





			def __mul__(  self ,  lowerCAmelCase__		)	->   Polynomial:

							'''simple docstring'''


							__lowercase					     =				[0] * (self.degree + polynomial_a.degree + 1)
							for i in range(self.degree + 1		):
											for j in range(polynomial_a.degree + 1		):
															coefficients[i + j] += (
															    self.coefficients[i] * polynomial_a.coefficients[j]
															)

							return Polynomial(self.degree + polynomial_a.degree ,  lowerCAmelCase__		)





			def 			_SCREAMING_SNAKE_CASE     (  self ,  lowerCAmelCase__		)	->   int | float:

							'''simple docstring'''


							__lowercase					     =				0
							for i in range(self.degree + 1		):
											result += self.coefficients[i] * (substitution**i)
							return result





			def __str__(  self		)	->   str:

							'''simple docstring'''


							__lowercase					     =				''''''
							for i in range(self.degree ,  -1 ,  -1		):
											if self.coefficients[i] == 0:
															continue
											elif self.coefficients[i] > 0:
															if polynomial:
																			polynomial += " + "
											else:
															polynomial += " - "

											if i == 0:
															polynomial += str(abs(self.coefficients[i]		)		)
											elif i == 1:
															polynomial += str(abs(self.coefficients[i]		)		) + "x"
											else:
															polynomial += str(abs(self.coefficients[i]		)		) + "x^" + str(lowerCAmelCase__		)

							return polynomial





			def __repr__(  self		)	->   str:

							'''simple docstring'''


							return self.__str__()





			def 			_SCREAMING_SNAKE_CASE     (  self		)	->   Polynomial:

							'''simple docstring'''


							__lowercase					     =				[0] * self.degree
							for i in range(self.degree		):
											__lowercase					     =				self.coefficients[i + 1] * (i + 1)
							return Polynomial(self.degree - 1 ,  lowerCAmelCase__		)





			def 			_SCREAMING_SNAKE_CASE     (  self ,  lowerCAmelCase__ = 0		)	->   Polynomial:

							'''simple docstring'''


							__lowercase					     =				[0] * (self.degree + 2)
							__lowercase					     =				constant
							for i in range(self.degree + 1		):
											__lowercase					     =				self.coefficients[i] / (i + 1)
							return Polynomial(self.degree + 1 ,  lowerCAmelCase__		)





			def __eq__(  self ,  lowerCAmelCase__		)	->   bool:

							'''simple docstring'''


							if not isinstance(lowerCAmelCase__ ,  lowerCAmelCase__		):
											return False

							if self.degree != polynomial_a.degree:
											return False

							for i in range(self.degree + 1		):
											if self.coefficients[i] != polynomial_a.coefficients[i]:
															return False

							return True





			def __ne__(  self ,  lowerCAmelCase__		)	->   bool:

							'''simple docstring'''


							return not self.__eq__(lowerCAmelCase__		)
import datasets


__a    :	Optional[Any]         =    """\
@InProceedings{conneau2018xnli,
  author = \"Conneau, Alexis
                 and Rinott, Ruty
                 and Lample, Guillaume
                 and Williams, Adina
                 and Bowman, Samuel R.
                 and Schwenk, Holger
                 and Stoyanov, Veselin\",
  title = \"XNLI: Evaluating Cross-lingual Sentence Representations\",
  booktitle = \"Proceedings of the 2018 Conference on Empirical Methods
               in Natural Language Processing\",
  year = \"2018\",
  publisher = \"Association for Computational Linguistics\",
  location = \"Brussels, Belgium\",
}
"""

__a    :	Optional[Any]         =    """\
XNLI is a subset of a few thousand examples from MNLI which has been translated
into a 14 different languages (some low-ish resource). As with MNLI, the goal is
to predict textual entailment (does sentence A imply/contradict/neither sentence
B) and is a classification task (given two sentences, predict one of three
labels).
"""

__a    :	str         =    """
Computes XNLI score which is just simple accuracy.
Args:
    predictions: Predicted labels.
    references: Ground truth labels.
Returns:
    'accuracy': accuracy
Examples:

    >>> predictions = [0, 1]
    >>> references = [0, 1]
    >>> xnli_metric = datasets.load_metric(\"xnli\")
    >>> results = xnli_metric.compute(predictions=predictions, references=references)
    >>> print(results)
    {'accuracy': 1.0}
"""





def 							UpperCAmelCase		(       lowercase				,     lowercase				):







				"""simple docstring"""



				return (preds == labels).mean()




@datasets.utils.file_utils.add_start_docstrings(_DESCRIPTION		,_KWARGS_DESCRIPTION					)
class   _UpperCamelCase (		datasets.Metric					):


			"""simple docstring"""






			def 			_SCREAMING_SNAKE_CASE     (  self		)	->   str:

							'''simple docstring'''


							return datasets.MetricInfo(
							    description=_DESCRIPTION ,  citation=_CITATION ,  inputs_description=_KWARGS_DESCRIPTION ,  features=datasets.Features(
							        {
							            '''predictions''': datasets.Value('''int64''' if self.config_name != '''sts-b''' else '''float32'''		),
							            '''references''': datasets.Value('''int64''' if self.config_name != '''sts-b''' else '''float32'''		),
							        }		) ,  codebase_urls=[] ,  reference_urls=[] ,  format='''numpy''' ,  )





			def 			_SCREAMING_SNAKE_CASE     (  self ,  lowerCAmelCase__ ,  lowerCAmelCase__		)	->   Dict:

							'''simple docstring'''


							return {"accuracy": simple_accuracy(lowerCAmelCase__ ,  lowerCAmelCase__		)}